GPN 2024 Annual Meeting

Data Parallelism from Nvidia, taught by Michael Keith.

This workshop teaches you techniques for data-parallel deep learning training on multiple GPUs to shorten the training time required for data-intensive applications. Working with deep learning tools, frameworks, and workflows to perform neural network training, you’ll learn how to decrease model training time by distributing data to multiple GPUs, while retaining the accuracy of training on a single GPU. Prerequisites: Experience with deep learning training using Python.
Max 45 attendees